Performance evaluation of saliency map methods on remotely sensed RGB images

Download

index.pdf

Date

2016

Author

Sönmez, Selen

Metadata

Show full item record

Item Usage Stats

224
views

170
downloads

Predictive applications of human eye visualization so called saliency map computational models become more attractive in image processing studies. Saliency map highlights regions that are distinctive from their surrounding in the images in interest. In this study, various computational models for salient region detection are investigated on remotely sensed images. The computational methods considered are Itti-Koch, Graph-Based Visual Saliency, Saliency Detection by Combining Simple Priors, Frequency-tuned Salient Region Detection, Image Signature and Region Covariance based Saliency. For evaluation of the computational methods, a dataset containing 226 remotely sensed RGB images has been prepared. The dataset forestry and water surface images captured in three different levels. The saliency maps produced by the computational methods on the dataset are compared with the saliency maps extracted from data collected in experiment conducted on human subjects. In these experiments 20 subjects are participated and the data is collected by using Tobii T120 Eye Tracker device while the images in the dataset are presented to subjects on computer screen. In the performance evaluation, the saliency maps obtained from human subjects are used as ground truth. The performances of the computational methods are determined by computing similarity of their results to ground truth. As similarity measure, Cosine correlation, Pearson correlation and Structural Similarity index are used. Our experimental evaluation demonstrated that Region Covariance based Saliency and Graph-Based Visual Saliency are the best saliency methods among those that we considered for saliency map generation of remotely sensed RGB images.

Subject Keywords

Eye tracking., Digital maps., Remote sensing., Image processing., Cartographic materials., Remote-sensing images.

URI

http://etd.lib.metu.edu.tr/upload/12620020/index.pdf
https://hdl.handle.net/11511/25711

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Image fusion for improving spatial resolution of multispectral satellite images Ünlüsoy, Deniz; Süzen, Mehmet Lütfi; Department of Geological Engineering (2013) In this study, four different image fusion techniques have been applied to high spectral and low spatial resolution satellite images with high spatial and low spectral resolution images to obtain fused images with increased spatial resolution, while preserving spectral information as much as possible. These techniques are intensity-hue-saturation (IHS) transform, principle component analysis (PCA), Brovey transform (BT), and Wavelet transform (WT) image fusion. Images used in the study belong to Çankırı reg...
An Investigation on hyperspectral image classifiers for remote sensing Özdemir, Okan Bilge; Çetin, Yasemin; Department of Information Systems (2013) Hyperspectral image processing is improved by the capabilities of multispectral image processing with high spectral resolution. In this thesis, we explored hyperspectral classification with Support Vector Machines (SVM), Maximum Likelihood (ML) and KNearest Neighborhood algorithms. We analyzed the effect of training data on classification accuracy. For this purpose, we implemented three different training data selection methods; first N sample selection, randomly N sample selection and uniformly N sample se...
Performance Comparison of Different Sparse Array Configurations for Ultra-Wideband, Near-field Imaging Applications Cetin, Beyzat Talat; Alatan, Lale (2017-03-24) The aim of this study is to compare the performance of different multiple-input multiple-output (MIMO) array topologies, intended to be used in ultra-wideband (UWB) near-field imaging applications, by using an analysis method that does not include the effects of image reconstruction algorithm. For this purpose, maximum projection method, previously proposed for the analysis of UWB arrays under far-field conditions, is utilized and modified to obtain two way beam patterns of UWB arrays operating in the near-...
Eye tracking in multimodal comprehension of graphs Acartürk, Cengiz (2012-07-31) Eye tracking methodology has been a major empirical research approach for the study of online comprehension processes in reading and scene viewing. The use of eye tracking methodology for the study of diagrammatic representations, however, has been relatively limited so far. The investigation of specific types of diagrammatic representations, such as statistical graphs is even scarce. In this study, we propose eye tracking as an empirical research approach for a systematic analysis of multimodal comprehensi...
Efficient algorithms for convolutional inverse problems in multidimensional imaging Doğan, Didem; Öktem, Figen S.; Department of Electrical and Electronics Engineering (2020) Computational imaging is the process of indirectly forming images from measurements using image reconstruction algorithms that solve inverse problems. In many inverse problems in multidimensional imaging such as spectral and depth imaging, the measurements are in the form of superimposed convolutions related to the unknown image. In this thesis, we first provide a general formulation for these problems named as convolutional inverse problems, and then develop fast and efficient image reconstruction algorith...

Citation Formats

S. Sönmez, “Performance evaluation of saliency map methods on remotely sensed RGB images,” M.S. - Master of Science, Middle East Technical University, 2016.